Primary GBM, accounting for over 90% of human GBMs, develops rapidly or de novo with no prior clinical disease. Large-scale genomic analyses have contributed greatly to the definition of the overall glioma landscape and datasets (TCGA) have enabled the division of GBMs into subclasses based on their genomic, transcriptomic, and signal transduction patterns. Sadly, despite these insights into the genetics of the disease and advances in neurosurgery, radiation and chemotherapy, its dismal prognosis has not changed significantly. The current paradigm for glioblastoma (GBM) therapy is based on the concept that each patient is treated with a protocol that is most likely to prolong life (temozolamide and radiation) in a majority of patients. The treatment may not be efficacious for any given individual even though it may work with most patients with a similar pathology. If the treatment fails, second-line treatments, usually experimental are administered, although by this time it may be too late for many patients with glioblastoma. This concept is obviously unacceptable in the current era wherein the technology for whole genome sequencing is a reality and thus enabling personalized medicine using targeted agents based on genetic alterations of each patient is possible. Project 1 will investigate in mouse model using human GBM explants, if stratification of patients based on the four molecular classes of GBM followed by optimization of single and combination therapies for each of these subclasses can enhance outcomes. Project 2 using a mouse model of adult onset GBM, investigate the sequential accumulation of genetic lesions that initiate gliomagenesis and also identify genetic/proteomic alterations that transform a slow growing lesion into aggressive disease, as well as alterations that result in therapeutic resistance. This information will be used to test the hypothesis that targeted inhibition of initiating oncogenic pathways early in gliomagenesis will enhance survival. Project 3 will undertake prospective and retrospective GBM clinical trials to evaluate quantitative MR biomarker metrics for early prediction of treatment efficacy and GBM recurrence. The overall integration of the program components will provide novel insights into the oncogenic evolution of the disease (Project 2) and the application of targeted agents directed against these oncogenic events in an individualized manner (Project 1) with the use of novel imaging technologies as predictive surrogates (Project 3) will significantly impact this patient population. All three research projects will be supported by four cores, the administrative core (Core A), an imaging core (Core B), a bioinformatics core (Core C) and the biostatistics core (Core D).